code: def landmark_pred(boxes, landmark_deltas):
      if boxes.shape[0] == 0:
          return np.zeros((0, landmark_deltas.shape[1]))
      boxes = boxes.astype(np.float, copy=False)
      widths = boxes[:, 2] - boxes[:, 0] + 1.0
      heights = boxes[:, 3] - boxes[:, 1] + 1.0
      ctr_x = boxes[:, 0] + 0.5 * (widths - 1.0)
      ctr_y = boxes[:, 1] + 0.5 * (heights - 1.0)
      preds = []
      for i in range(landmark_deltas.shape[1]):
          if i % 2 == 0:
              pred = landmark_deltas[:, i] * widths + ctr_x
          else:
              pred = landmark_deltas[:, i] * heights + ctr_y
          preds.append(pred)
      preds = np.vstack(preds).transpose()
      return preds
  
file_path: insightface/detection/retinaface_anticov/rcnn/processing/bbox_transform.py
imports: import numpy
  from ..cython.bbox import bbox_overlaps_cython
label_desc: Use image node_id 7 for calling a global function with example usage: landmark_pred(boxes, landmark_deltas) and returns: preds, np